مكاتیب رسول اور عربی خط نویسی

Islam has borne a deep and lasting impact on all aspects of human life. Inevitably language, which is a crucial factor in the build-up of society, has also been re-vitalized and re-invigorated by Islam. It was Arabia where Islam dawned its early rays, hence it is the Arabic language that got evolved under the revolutionary spirit of Islam. This deep impact has been caused through the two basic sources of Islam i. e. Quran and Hadith. Since our focus is Hadith, hence we shall talk on the impact of Hadith on the Arabic language. Hadith has a lasting influence on the Arabic language, its literature, and the various genres of the Arabic literature. The topmost among these diverse genres that dramatically evolved under the impact of Islam is 'letter writing'. The genre of letter writing has been passing through its evolutionary stages before the Prophet-hood of Muhammad (S. A. W) . Yet the clarity and style that it adopted; the purposefulness that it aspired and opted for; and its utility as an important official correspondence document all happened in the hands of our Holy Prophet (S. A. W) . In short, it turned into a regular genre of literature. Letter-writing owes deeply to the life infusing spirit of our Holy Prophet (S. A. W) for its lay-out and design, its aim and purpose, and basic features. Our Holy Prophet (S. A. W) left a lasting impact on the letter writing that shall always be a source of inspiration for the faithful.

A Framework to Predict the Student S Performance in Programing Courses

Academic grades prediction is considered as one of the hot research areas since last decade, which comes under the domain of educational data mining. It has been observed that in undergraduate computer science programs, programming courses are considered challenging. This results in higher tendency of earning lower grades, failures or drop-outs than other computer science subjects. An early prediction of the students who have high probability of failure (known as at-risk students) will enable the instructors to intervene and provide extra guidance to learners. An accurate prediction of student?s grades can directly influence the overall quality of any degree program and the retention rate of the institution. This research presents a machine learning based classification model for undergraduate students grades prediction, enrolled in any programming course(s) in traditional education system. The proposed model is built after careful collection and pre-processing of data, appropriate feature selection, and model evaluation based on four metrics namely accuracy, precision, recall and F1-score. Six widely used supervised machine learning techniques including Random Forest, Artificial Neural Network, K-Nearest Neighbors, Na?ve Bayes, Ordinal Regression, and Support Vector Machine are used after tuning and optimization. The data used for this research is collected from a private sector university in Lahore. The collected data covers two major domains: student?s academic record and demographic data. The results show that Support Vector Machine and K-Nearest Neighbors give highest scores (ranging from 81% to 94%) for all the evaluation metrics and for all the seven programming courses considered for this study.